Neural response system

ABSTRACT

A neural response system, including a plurality of filters for each receiving and filtering a plurality of tilt response signals obtained from a person; a segmenter for segmenting the filtered response signals into time segments; and a neural event extractor for performing a neural event extraction process on each of the time segments to obtain and generate biomarker data representing a plurality of biomarkers for each segment.

FIELD

The present invention relates to a neural response system that canprovide biological data indicative of a number of disorders usingelectrovestibulography.

BACKGROUND

Systems have been developed to obtain an auditory evoked response (AER)or brainstem auditory evoked response (BAER) for a patient representingactivity of the patient's auditory system. The AER is an electricalbrain wave or neural response obtained from electrodes placed on thepatient in response to a stimulus, normally a sound. Depending on thelatency of the response and the placement of the electrodes, differentclasses or types of AERs can be obtained. Those with the shortestlatency are generated by the inner ear and the auditory nerve, and arereferred to as electrocochleography (“ECOG” or “ECochG”) responses. Thenext response reflects activity within the auditory brainstem and isreferred to as an auditory brainstem response (ABR). Further detail isprovided in Hall, James W, III; Handbook of Auditory Evoked Responses;Allyn and Bacon; Needham Heights, Mass., 1992.

Electrocochleography systems are currently used to perform diagnoses ofthe cochlea and vestibular apparatus. In the case of the vestibularsystem, recently analysis for this specific part of the ear has beenreferred to as electrovestibulography (EVestG), being a distinct variantof ECOG. The systems are used to produce a patient neural response whichinvolves placing a recording electrode as close as practical to apatient's cochlea. An acoustic transducer, eg an earphone, is used toprovide an auditory stimulus to evoke the response. For EVestG thepatient is however tilted, in different directions, to evoke a specificresponse from the vestibular apparatus. It is not necessary to also usean auditory stimulus for EVestG. A distinct EVestG signal, similar to anECOG signal but representing the neural response from the vestibularapparatus, is used to determine an Sp/Ap ratio that can be used for thediagnosis of a number of conditions, particularly Meniere's disease. Thefirst wave, normally labelled N1, of the response signal is examined todetermine the summating potential (Sp), the action potential (Ap) andthe second summating potential (Sp2), as shown in FIG. 1. The responseis only of the order of a few μV and is received with considerableunwanted noise making it difficult to determine and isolate.

International patent publication WO 2006/024102 to Monash Universitydescribes an ECOG system to extract neural event data that can be usedto indicate whether a person has Meniere's, Parkinson's disease ordepression. The system produces biological marker data representing theSp/Ap ratio and a TAP marker that can be used to indicate the presenceof a disorder. To assist with identification of a wide variety ofneurological and neurodegenerative disorders it would be advantageous toprovide at least a useful alternative or in particular a system that isable to provide additional biological marker data for a person that canbe used for different disorders.

SUMMARY

In accordance with the present invention there is provided a neuralresponse system, including:

a plurality of filters for each receiving and filtering a plurality oftilt response signals obtained from a person;

a segmenter for segmenting the filtered response signals into timesegments; and

a neural event extractor for performing a neural event extractionprocess on each of the time segments to obtain and generate biomarkerdata representing a plurality of biomarkers for each segment.

The present invention also provides a neural response process,including:

receiving and filtering, using a plurality of filters, a plurality oftilt response signals obtained from a person;

segmenting the filtered response signals into time segments; and

processing each of the time segments to obtain and generate biomarkerdata representing a plurality of biomarkers for each segment.

The present invention also provides a neural response system, including:

a neural response processor for processing time segments of tiltresponse signals obtained from a person to obtain biomarker datarepresenting a dynamic phase of each tilt response signal; and

a diagnostic tool for processing the biomarker data to determine whethersaid person has a neurological condition.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the present invention are hereinafterdescribed, by way of example only, with reference to the accompanyingdrawings, wherein:

FIG. 1 is a representation of Sp, Ap and Sp2 points related to the firstwave of a generalized ECOG response signal from an ECOG system anddefines the summating potentials Sp and Sp2 and the action potential Ap;

FIG. 2 is a schematic diagram of a preferred embodiment of an EVestGsystem connected to a patient;

FIG. 3 is a representation of the raw data for an EVestG signal producedby a tilt sequence of the system;

FIG. 4 is a diagram of a neural event extractor and a neural eventextraction process performed by an analysis module of the system;

FIG. 5 is an architecture diagram of filters and a segmentationcomponent of the system;

FIG. 6 is a diagram of a Sp/Ap curve generated by the system;

FIG. 7 is a schematic diagram of biomarkers obtained from data of anEVestG plot;

FIG. 8 is a diagram of a diagnostic tool and process of the system;

FIG. 9 is a diagram of biomarker thresholds used for indicating adisorder;

FIG. 10 is a diagram of a Sp/Ap curve generated by the system before andafter the taking of a pharmaceutical compound (L-dopa) by a sufferer ofParkinson's disease;

FIG. 11 is a diagram of a Sp/Ap curve generated by the system before andafter exposure of a clinically depressed subject to a series of physicaltherapy (Transcranial Magnetic Stimulation);

FIG. 12 is a diagram of a Sp/Ap curve generated by the system showingdistinct DC shifts for a subject suffering from Meniere's disease; and

FIG. 13 is a diagram of a Sp/Ap curve generated by the system showing alack of DC shifts for a subject with BPPV.

DETAILED DESCRIPTION

An electrovestibulography (EVestG) system 2, as shown in FIG. 2,provides a neural response system that is able to generate a biologicalmarker, or biomarker, data representing over 5,000 biomarker measuresfrom a patient 4 subjected to involuntary tilt movements in a tilt chair6. The biomarker data is generated by signal processing analysis ofEVestG signals produced in response to the stimulus provided by theinvoluntary tilts.

An EVestG signal is obtained from electrodes 10, 12 and 14 electricallyconnected to an amplifier circuit 22 of a computer system 20 of thesystem 2. A first electrode 10 (eg a ECochG Electrode produced byBio-Logic Systems Corp (http://www.blsc.com/pdfs/HearCatalog.pdf) isplaced on the tympanic membrane of an ear of a patient 4. A secondelectrode 12 is placed on the patient's earlobe, as a reference point,and a third electrode 14 is connected to the patient's forehead and tothe common point of the amplifier. A shield connection 16 is also madeto an electrical isolation shield 18 normally placed around the testingroom. The shield 18 is connected to the shield of the amplifier 22. Thetesting room is a sound attenuated booth. The booth may include theamplifier 22 with the rest of the computer system 20 placed outside thebooth and connected to the amplifier 22 by a USB connection.

The patient 4, as shown in FIG. 2, is placed on the chair 6, such as arecliner lounge chair, that allows the patient's head to rest passivelyand supported securely to relax the subject during the testing cycle.Electrically powered tilt chairs have been specifically produced byNeuro Kinetics Inc. (http://www.neuro-kinetics.com) that enable apatient to be tilted and produce a response to this stimulus which isless corrupted by muscle artifact. An involuntary head tilt can beobtained by an assistant manipulating the chair 6 so as to induce thehead tilt without any patient neck muscle activity. Alternatively, thetilt chair can be fitted with and controlled by hydraulic components toinvoke a predetermined set of involuntary tilt sequences.

A hydraulically actuated chair is used and configured to ensure strayelectric fields caused by the actuation of electrical servo-motors areeliminated as far as possible from being generated in the testing booth.The hydraulically actuated chair is used to provide the tilts withoutproducing either neck muscle artefacts or stray electric fields that maycorrupt sensitive signal measurements. To reduce ocular artefacts, thepatient is also asked to keep their eyes closed during the testingcycle. The head is tilted down to approximately the same angle as amaximum voluntary head tilt that can be achieved by the patientthemselves. An EVestG signal or tilt response is obtained for each tiltsequence. The tilts, or tilt sequences, are up/down (patient upright andprone), forward/back, ipsilateral, contralateral, and rotation (patientupright and prone).

The tilts each produce a raw EVestG response signal, as shown in FIG. 3.The tilt sequences performed by the chair 6 are controlled so that theEVestG response signal obtained is divided into 15 time epochs orsegments, but this can be reduced or increased. The neural responseproduced on electrodes 10 to 14 is continuously recorded by the system2. The EVestG neural response signal for each tilt is a time domainvoltage signal having multiple frequency components. The main componentsof interest are up to 22,500 Hz. In particular the Sp peak (depending onthe signal to noise ratio (S/N)) is only a few samples wide. Accordinglya sampling rate of 44.1 kHz is required during the test cycle as thisrate has sufficient sensitivity to recognise and record this event withadequate accuracy by the system 2. This sampling rate can be higher than44.1 kHZ, and the system 2 would then require faster signal processingcomponents. The seven tilts are performed with two sets of electrodes 10to 14 positioned respectively for the left ear of the patient and theright ear of the patient. This provides left and right datasimultaneously for each ear for each of the seven tilts. Both ears aretested in both dynamic and static phases of all tilt maneuvers, as aneurological disorder can exist in either hemisphere of the brain, andmay only reveal its presence by comparison of each sides response insimilar excitatory or inhibitory phases of one or other of the left andright vestibular apparatus. Such versatility is required if thediagnostic test is to recognise differences in evoked response betweeneach hemisphere of the brain, where in some neurological disordersasymmetry of functioning can occur, (e.g. as for Parkinson's disease).

The sequence for each tilt is to record firstly for 20 seconds with thepatient in the tilt chair resting the head/neck against a neck rest andrecording a background (BG) signal segment 402 for t=20 seconds. Thissegment 402 includes a BGi segment which is 1.5 seconds immediatelyprior to the occurrence of tilt. The patient is then tilted through 45°to come to rest after 2 to 3 seconds. This gives an onset (On) segment404 for t=20-25 seconds, an onset transient (OnT) segment 406 fort=20-30 seconds, and steady state (SS) segment 408 for t=30-40 seconds.The semicircular canals of the ear function to detect the onset of headmovement, and by analysing approximately 5 seconds from a signalrecorded at the onset of the head tilt (the On segment) assists withdetermining the response generated by the semicircular canals. The onsetresponse includes two additional segments, the movement (OnA) segment410 and the post movement (OnB) segment 412, which occur at t=20-23seconds and t=23-25 seconds respectively. The OnA segment 410 can bedivided to provide an additional OnAA segment 413 for the first 1.5seconds after tilt and an OnBB segment 415 for the next 1.5 secondsafter tilt. The OnAA and OnBB segments are selected to be 20-21.5 and21.5-23 seconds respectively for increased separation of theacceleration and deceleration components that these segmentsrespectively represent. The times are selected to take into accountlatency of the hydraulic chair 4 of 0.6-0.8 sec. These segments includeresponses produced by the semicircular canals and the otolithic organs.The driven semicircular canal response ceases after about 10 seconds,and accordingly the first 10 seconds are therefore considered as theonset transient (OnT) where this decay is observed. The otolith organs,on the other hand, function to maintain static balance, or balanceduring steady unidirectional movements. The steady state (SS) segment408 can therefore be analysed to provide the driven response of theotolithic organs separately.

The sequence for the tilt is completed at t=40 seconds by then returningthe patient to the original position. The patient is returned to theoriginal position over 1 to 2 seconds and the response produced canagain be segmented in a similar manner. The segments for the return partof the tilt sequence:

(i) Upwards Onset (UpOn) 420 for t=40-45 seconds;

(ii) Upwards Onset Transient (UpOnT) 422 for t=40-50 seconds;

(iii) Upwards Steady State (UpSS) 424 for t=50-60 seconds;

(iv) Upwards Acceleration (UpOnA) 426 for t=40-43 seconds;

(v) Upwards Deceleration (UpOnB) 428 for t=43-45 seconds;

(vi) UpOnAA 427 for t=40-41.5 seconds; and

(vii) UpOnBB 429 for t=41.5-43 seconds.

The upOnAA segment is selected to be 40-41.5 seconds for increasedseparation of the acceleration component, and the upOnBB segment to be41.5-43 seconds for increased separation of the deceleration component.Again the times are selected to take into account hydraulic chairlatency of 0.6-0.8 sec.

The seven tilt sequences, or tilts, are:

-   -   (i) Up/Down. The chair 6 is moved so as to accelerate the        patient's body vertically with patient's head in a normal        upright position, and then returned.    -   (ii) Up/Down Prone. The chair is moved so as to accelerate the        patient's body vertically with the patient's head and body in a        prone or lying down position, and then returned.    -   (iii) Forward/Back. The patient's body is tilted from a rest        position backwards through 45°, and then returned.    -   (iv) Ipsilateral. The patient's body is moved through 45 degrees        ipsilaterally to the electrode 10, and then returned: If the        electrode 10 is in the left ear the tilt is to the left then the        tilt is back to the right. For the right ear the tilt is to the        right.    -   (v) Contralateral. The patient's body is moved 45 degrees        contralateral to the electrode 10, and then returned. For        instance, if the electrode 10 is in the left ear, the tilt is to        the right and the patient is returned. For the right ear the        tilt is to the left.    -   (vi) Rotation. The patient's body is rotated between 45 and 90        degrees to the right, and then returned, with patient's head in        a normal upright position.    -   (vii) Rotation Prone. The patient's body is rotated between 45        and 90 degrees to the right, and then returned, with the        patient's body in a prone or lying down position.

During all movements the head and neck are not moved relative to thebody. The whole body is moved to reduce muscle artefacts. Alternatively,the tilts may be performed by having the subject lie down on their backand tilting their body through ipsilateral, contralateral, vertical andbackward directions. These tilts produce less muscle artefactsparticularly for the ipsilateral and contralateral tilts.

The computer system 20 of the EVestG system 2 includes the amplifiercircuit 22 and a communications module 24 for handling the data outputof the amplifier 22 and then storing the response as a voltage signalover time as a wave file using a computer program such as Adobe Audition(http://www.pacific.adobe.com/products/audition/main.html) provided by acapture module 26. The amplifier 22 includes a CED 1902 isolatedpre-amplifier circuit and a CED Power 1401 analogue to a digitalconverter (ADC). Both the CED 1902 and CED 1401 ADC are produced byCambridge Electronic Design Limited (http://www.ced.co.uk). The CED 1401ADC has an excellent low frequency (less than 1 Hz) response. Thecomputer system 20 further includes an analysis module 28 and a displaymodule 30. The analysis module 28 provides a neural event extractor 400and includes computer program code (eg. MATLAB® code,http://www.mathworks.com) responsible for performing a neural eventextraction process (NEEP) of the extractor 400, as shown in FIG. 4, inconjunction with the other software modules. The analysis module 28 alsoprovides a number of different filters used to filter the responsesignal samples, as discussed below. This filtering may include theremoval of the system (or White Noise) response of the feature detectioncomponents of the neural event extraction process.

The graphics display module 30 generates a user interface 32 for anoperator of the system 2 to provide input controls so that the operatorcan control the neural event extraction process (NEEP), and to generatedisplays of neural event data, such as the Sp/Ap plot shown in FIG. 6.The computer program code of the software modules 24 to 30 are stored onmemory of the computer system 20 and are run on an operating system 34,such as Microsoft Windows or Linux. The hardware used may include theamplifier circuit 22 and a standard personal computer 20, such as thatproduced by IBM Corporation (http://www.ibm.com). ECOG recording systemsare produced by Bio-Logic Systems Corp (http://www.blsc.com/hearing/).Whilst the neural event extraction process (NEEP) may be performed underthe control of the software of the modules 24 to 34, it will beunderstood by a skilled addressee that steps of the process can beperformed by dedicated hardware circuits, such as ASICs and FPGAs, andalso performed by components or modules distributed across a computercommunications network, such as the Internet. For example, dedicatedfilter circuits can be used to provide the filters, and dedicateddigital signal processors (DSPs) can be used to perform a number of thesignal processing steps to enhance the processing speed.

The neural event extraction process (NEEP), as shown in FIG. 4, is thesame as that described in WO 2006/024102 for an EvestG response, exceptfor the recording filtering, and segmenting process 440, and thebiomarker extraction process 450. The data representing the EVestGresponses obtained from each of the seven tilts and for each ear of apatient, i.e. 14 responses, is recorded, as discussed above, and thenfiltered three different ways to provide filtered data for threefiltered responses for each tilt response, i.e. filtered response datafor 42 filtered tilt responses. A shown in FIG. 5, the tilt responses ofeach tilt 501, 502, 504, 506, 508, 510 and 511 are each filtered by afirst filter 512, a second filter 514 and a third filter 516. The firstfilter 512 provides no filtering, as it allows all frequencies to pass,including the data representing DC voltage levels. It does, however,include a very narrow notch filter which introduces no phase shifts butremoves power line harmonics, e.g. at 50 Hz or 60 Hz, and also removeshydraulic (proportional valve) switching artefacts that may beintroduced by hydraulic actuation of the chair. This notch filter isalso employed at the output of the second and the third filters 514 and516. The second and third filters 514 and 516 both provide high passfiltering. The second filter 514 includes a 5 Hz high pass filter andthe third filter 516 includes a 120 Hz high pass filter. Providing thethree filtered tilt responses produced by the filters 512, 514 and 516for processing by a neural event extraction process (NEEP) gives thebenefit that groups of biological markers that can be corrupted by lowfrequency data are enhanced in the high pass filtered responses, whereasother critical biological markers that are only present or can only beextracted when the low frequency data is present are also available,e.g. the biological markers used for Meniere's disease.

The 42 filtered tilt responses are each segmented by a segmentationprocess 440 performed by segmenter 550 of the module 28 in order toproduce the fifteen segments 402, 404, 406, 408, 410, 412, 413, 415,420, 422, 424, 426, 427, 428 and 429 for each filtered tilt response, asdiscussed above. This produces 630 sets of data representing 630filtered tilt response segments. The segments comprise data obtainedform the left ear of the patient 552 and data obtained from the rightear of the patient 554. The output of the record, filter andsegmentation process 440 is the 630 filtered tilt response signals thatare each then subjected to the remaining processes of the neural eventextraction process (NEEP) shown in FIG. 4. This produces Sp/Ap data foreach segment, i.e. for each of the 630 sets of data. The segments areeach treated as an EVestG response by the neural event extractionprocess (NEEP). As discussed in WO 2006/024102, the process decomposeseach response segment using a complex Morlet wavelet to obtain phasedata across seven equally logarithmically space scales from 600 Hz to 12KHz. The scale data is processed to determine loci where sharp changesin phase occur across all scales.

However, a large phase change may be indefinable across the scales butat more than one (or slight variations in) sample time. At scale 1, forexample, a locus could be found at say time sample 344. For scale 2 theloci might be at scale 345, scale 3 at loci 347, scale 4 loci 349, scale5 loci 346, scale 6 loci 345 etc. This represents a curved connection ofpoints across the scales relating the same phase change. To cater forthis the NEEP allows for and applies an acceptable gap between scalesample times. This gap may be arbitrarily set, but is typically 1 to 3samples.

Once these loci are discriminated, characteristic data for a Sp/Ap plotis derived and used to select neural responses from artefacts. The datafor a Sp/Ap curve is determined by averaging the loci determined acrossthe scales, and an EVestG plot can be produced from the data for eachsegment as shown in FIG. 6.

The neural event extraction process (NEEP) can inadvertently detect locidue to White noise. To address this and improve the S/N ratio of theextracted EVestG Sp/Ap plot the white noise response can be subtractedby the system 2. The system 2 achieves this by first inputting whitenoise filtered to match the recording characteristics of the system (eg.10 kHz low pass and no (DC), 5 or 120 Hz high pass filtering) andrecording the EVestG Sp/Ap system response to this input, which isstored as a Band Limited White Noise (BLWN) response. A scaled BLWNresponse is then subsequently subtracted from the EVestG (RAEVestG)produced by the NEEP. The scaling factor is decided by determining theAp point of the RAEvestG. The scaling factor is set to 0 and incrementedin 0.01 steps until the Output data=RAEVestG minus the scaled BLWNresponse sees the Ap point (response plot minima) shifting by more thanan arbitrary time, typically 2 samples. Once subtracting the scaled BLWNresponse causes a marked adjustment in the position of the Ap point, thescaling factor (scale) is set and not increased any further. This givesan adjusted NEEP Output EVestG=RAEVestG-scale*BLWN. The BLWN response isproduced by the NEEP processing the white noise response with thethreshold in step 318 set so that significant field potentials aredetected to characterise the BLWN response.

Sometimes neural events (field potentials) occur so that their waveformsoverlap. When this occurs the diagnostic biomarkers can becomecorrupted. To solve this problem the neural event extraction process(NEEP) can exclude such events without loss of biomarker integrity. Tofind these events the loci of the Ap points are determined. If theseloci are closer than an arbitrary number of samples typically 66 samples(1.5 ms) both field potentials can be excluded. A flag can be set orreset so that the exclusion decision can be switched in or out as partof the NEEP processing.

Once the Sp/Ap or EvestG curve data is produced for each segment (350),the extraction process is able to invoke a biomarker extraction process(450) on each segment that generates metric data or biological markerdata representing 17 different biological markers. As there are 630different segments produced for each patient, this gives rise tobiological marker data representing 630 measures of each biomarker.Accordingly, the biomarker data for each patient represents 10,710biomarker measures. This is a considerable amount of data obtained fromone patient subjected to the seven tilt sequences and can be used toaccurately determine the presence or not of a wide variety ofneurological and neurodegenerative disorders. The 17 biological markersare as defined below and illustrated in FIG. 7 (and given thedefinitions Ap is the whole V shaped EVestG curve; and the Ap point isthe lowest point of the Ap plot):

-   -   (i) Pre Ap Elevation or Depression. An elevation or depression        above/below the baseline immediately preceding the Ap.    -   (ii) Post Ap Elevation or Depression. An elevation or depression        above/below the baseline immediately after the Ap.    -   (iii) Ap Magnitude. The voltage magnitude at the Ap point.    -   (iv) Sp notch point (loci). The time at which the downward arm        of the Ap reverses/slows/stops, typically about 0.3 ms after Ap        onset.    -   (v) Start point (loci). The time of commencement of the Ap.    -   (vi) Baseline width. The width of the Ap at the baseline level.    -   (vii) Sp peak. The tip of the short rise after the Sp notch        point before the continuation downwards of the Ap towards the Ap        lowest point.    -   (viii) Sp width. The width (time) from the Sp notch to the next        downward arm of the Ap.    -   (ix) Sp Magnitude. The height of the Sp peak above the Sp notch        point.    -   (x) TAP (internal). The width (time) of the Ap at the Sp notch        level measured from the downward arm of the Ap after the Sp        notch horizontally to the upward arm of the Ap.    -   (xi) TAP (notch). The width (time) of the Ap at the Sp notch        level measured from the Sp notch horizontally to the upward arm        of the Ap.    -   (xii) Na angle. The angle of the downward arm of the AP between        the Ap lowest point and the height of the Sp notch measured from        vertical to that arm.    -   (xiii) K angle. The angle of the upward arm of the AP between        the Ap lowest point and the height of the Sp notch measured from        vertical to that arm.    -   (xiv) Na+K angle. Sum of the eleventh and twelfth biomarker        values.    -   (xv) Sp/Ap ratio. Vertical distance from Sp notch to baseline        divided by vertical distance from Ap point to baseline.    -   (xvi) Spike Rate. The number of field potentials detected and        used to form the Ap plot.    -   (xvii) DC Shift. The vertical shift between different Ap plots        measured from the baseline level, as shown in FIGS. 12 and 13.

An additional two biomarkers for each of the 42 filtered tilt responsesignals is obtained by subtracting the data obtained in the OnAA andOnBB segments from the BGi segment for each response signal. Thisproduces:

(a)BGi−OnAA response data, and(b)BGi−OnBB response data.

This produces 84 additional biomarkers representing the dynamic responseof each of the respective tilt response signals.

The analysis module 28 also provides a diagnostic tool 800 whichperforms a diagnostic process, as shown in FIG. 8, for a number ofdifferent disorders. The diagnostic process for each disorder involvesfirst determining (based on a processing control data) whether thebiological marker data for a patient is to be compared with that offingerprint biological marker data for a normal person without thedisorder (802). If not, the process proceeds to step 814, but otherwiseif it is to be so compared, then the biological marker data for a firstrecorded segment is compared with the normal fingerprint data (804). Thecomparison is a statistical process that looks for deviations, and anydeviations obtained from the fingerprint biomarkers are recorded asbiomarker deviations for that particular biomarker. Step 810 determineswhether the last 630^(th) segment has been processed, and if not, thebiological marker data for the next segment (812) is accessed and thecomparison process performed (804). The deviation data can be recordedas a log at step 806 or simply a sum maintained of the number ofdeviations for a particular biomarker. Once all the 10,710 biomarkermeasures have been compared, a determination is made at step 814 as towhether the biomarker data needs to be compared with fingerprintedbiological marker data for a person having the disorder. If so, then asimilar comparison process is performed, where the biological markerdata for the first segment is accessed and compared with the disorderfingerprint data (816). Again, a statistical analysis process isperformed, but this time to determine and record similarities betweenthe biological markers for each segment (818). Biological marker datafor the patient that is similar to that of the disorder segment isrecorded, again as a data log or by simply summing the similarities foreach biomarker. Once the last segment (the 630^(th) segment) has beenaccessed, as determined at step 820, the process then ends (824),otherwise the next segment is accessed (822) and the comparison process816 and recording process 818 completed again.

The deviation and/or similarity data obtained from the diagnostic tool800 can then be used to generate a report indicating whether or not thepatient has a disorder. For example, a pathology profile probability canbe generated as a result of the data produced by the diagnostic process.For example, to indicate that a patient may have or has Parkinson'sdisease, the diagnostic process needs to produce deviation data forparticular biomarkers that exceeds respective thresholds levels or sums.FIG. 9 is an example of the number of biomarker measures that are onaverage different for a patient with Parkinson's Disease when comparedwith biomarker measures for a normal patient or normal control measures.As shown in FIG. 9, the disorder fingerprint data for Parkinson'sdisease requires the 16 biomarkers to each exhibit recorded deviationsfor a pre-determined number of segments and tilts. For instance, the Kangle biomarker would on average record approximately 62 deviations fromnormal, the Na and K angles biomarker on average approximately 68deviations from normal, and the Sp/Ap ratio biomarker on averageapproximately 80 deviations from normal within the 630 responsesegments. To reduce processing time, only the best three to fivebiomarkers may be used to assess or determine a condition.

The system 2 is able to produce biomarker data indicating the presenceof neurodegenerative disorders or diseases which are irreversiblediseases where structures and functions of a part of the nervous systemeg brain, spinal column and nervous pathways, break down or aredestroyed by chemical, physical or biological action. Examples ofneurodegenerative diseases are Multiple Sclerosis, Parkinson's Disease,Creutzveldt Jacob Disease, Schizophrenia, Huntington's Chorea, Dementiaand Alzheimer's disease.

The system 2 is also able to produce biomarker data indicating thepresence of neurological disorders that may or may not be irreversiblebut result in malfunctioning of neural functions and result inpsychological and/or physiological manifestations of abnormalbehavioural or physical behaviours. Such disorders include Meniere'sdisease, BPPV, trauma, phantom pain and clinical depression (unipolarand bipolar).

The system 2 is also able to produce biomarker data indicating thepresence of drugs that may or may not have a reversible effect butresult in malfunctioning of neural functions and result in psychologicaland/or physiological manifestations of abnormal behavioural or physicalbehaviours. Such disorders include the presence of alcohol (for example:60-90 ml of 40% Alcohol/Volume), medications (SSRI's (selectiveserotonin reuptake inhibitors), L-dopa morning daily medication doses)and illicit drugs.

BPPV is benign positional paroxysmal vertigo, a balance disorder of theinner ear where small calcium crystals become displaced from theotolithic organs (saccule, utricle) and lodged, typically, in one of thesemi circular canals. The biomarkers particularly important in producingfingerprint data and used in the diagnostic process include the Sp/Apratio, spike rate and DC shift. For example, as shown in FIG. 13, the DCshifts can be determined and are much smaller or not present for apatient suffering BPPV for the canal affected. The Sp/Ap plots of FIG.12 with the significant DC effects are typical of that produced by apatient not suffering BPPV.

Meniere's disease is a balance disorder of the inner ear where the fluidin the semi-circular canals becomes more viscous and/or more copious asto change the freedom of the hair of the inner ear to react to movement.The biomarkers particularly important in producing fingerprint data andused in the diagnostic process include the Sp/Ap ratio, spike rate andDC shift, and BGi—OnBB response.

Parkinson's disease is a neurodegenerative disease affecting the basalganglia of the brain.

It is associated with the depletion of the availability of dopamineduring neural functioning. Its effects on the sufferer are treated byorally administered L-dopa, an intermediate in Dopamine(neuro-transmitter) synthesis. The biomarkers are particularly importantin producing fingerprint data and used in the diagnostic process includeTAP (internal) from the contralateral tilt, Baseline width, spike rate,and Start point loci, and BGi—OnBB response.

Schizophrenia is a neurological disorder associated with behaviouralproblems of the sufferer and the presence of symptoms such as hearingvoices and delusions. A sufferer can have a genetic predisposition tothe disease or it can be induced from substance abuse.

Excess levels of the neurotransmitter dopamine are also associated withthe disorder. The biomarkers particularly important in producingfingerprint data and used in the diagnostic process include, Ap pointmagnitude (providing a measure of response synchrony), contralateral andipsilateral TAP (internal), Baseline width, spike rate, Sp peak, Spnotch point loci, the Na and K angles Start point loci, and BGi—OnBB andBGi—OnAA response.

Clinical depression is a state of intense sadness, melancholia ordespair that has advanced to the point of being disruptive to anindividual's social functioning and/or activities of daily living. Thebiomarkers particularly important in producing fingerprint data and usedin the diagnostic process include, contralateral and ipsilateral TAP(internal), Baseline width, spike rate, Sp peak, Sp notch point loci,the Na and K angles and Start point loci, and BGi—OnBB and BGi—OnAAresponse.

Huntington's Chorea is a rare hereditary disorder of the basal gangliacausing progressive motor in-coordination, abnormal involuntarymovements (chorea), and intellectual decline. The biomarker datarequired is similar to that for Parkinson's Disease.

Alzheimer's disease is a common disease causing intellectual decline.The biomarker data required is similar to that for Parkinson's Disease.

Drug sensitivity has been tested, for example, for SSRI's (selectiveserotonin reuptake inhibitors) and Dopamine. When L-Dopa, i.e. Levodopa,is applied to Parkinson's disease patients the responses tend to morenormal, as shown in FIG. 10, so the same fingerprint biomarkers as forParkinson's disease are used to monitor the drug efficacy. Similarly fordepression, the same fingerprint biomarkers for depression are monitoredto determine the effectiveness of antidepressants (SSRI's).

Therapeutic sensitivity to physical therapy, such as transcranialmagnetic stimulation (TCMS) can also be determined using the biomarkerdata. When TCMS has been applied to clinically depressed patients theresponses tend to more normal, as shown in FIG. 11, so that changes tothe same fingerprint biomarkers as for clinically depressed subjectstowards a more normal profile can be used to monitor the efficacy of theTCMS therapy.

The biomarker data produced by the system 2 can also be used todetermine the dynamic nature of a patient's response without referenceto fingerprint biomarker data for a normal condition or a disorder. Forexample, the sum of the Na and K angles can be 10° different betweenipsilateral and contralateral tilts (i.e. excitatory tilts andinhibitory tilts), but for a patient suffering Meniere's disease thechange in the angles between the two tilts is on average much higher.Accordingly, a condition or disorder can be indicated or determined bysimply observing the biomarker data obtained dynamically betweendifferent tilts.

In addition to the Na and K angle summation there are various othercombinations and subsequent processing of the biomarkers measures thatcan be performed to provide additional biomarker data for indicating ordetermining a disorder or condition.

Many modifications will be apparent to those skilled in the art withoutdeparting from the scope of the present invention as herein described,with reference to the accompanying drawings.

1. A neural response system, including: different types of filters eachconfigured to receive and filter a plurality neural response signalsobtained from a person under different conditions; a segmenter forsegmenting each of the filtered response signals into time segments; anda neural event extractor for performing a neural event extractionprocess on each of the time segments to obtain and generate biomarkerdata representing a plurality of biomarkers for each segment, thebiomarker data for determining whether said person has a condition.
 2. Aneural response system as claimed in claim 1, wherein the neuralresponse signals are obtained from at least one electrode connected toat least one ear of the person subjected to a plurality of tiltsequences in a tilt chair.
 3. A neural response system as claimed inclaim 1, wherein the filters include at least one of a notch filter tosubstantially pass all frequencies, a first high pass filter and asecond high pass filter.
 4. A neural response system as claimed in claim3, wherein the cut-off frequency for the first filter is about 5 Hz andthe cut-off frequency for the second filter is about 120 Hz.
 5. A neuralresponse systems as claimed in claim 1, wherein the neural eventextractor generates curve data representing a Sp/Ap field potentialcurve for each segment.
 6. A neural response system as claimed in claim5, wherein the biomarker data is determined using the curve data and thebiomarkers represent relationships and constants associated with thefield potential curve.
 7. A neural response system as claimed in claim5, wherein the biomarker data is determined using the curve data and thebiomarkers represent spike rates, and time and voltage measurements ofthe field potential curve.
 8. A neural response system as claimed inclaim 5, wherein the biomarker data is determined using the curve dataand the biomarkers represent ratios, angles and areas associated withthe field potential curve.
 9. A neural response system as claimed inclaim 1, including a diagnostic tool for comparing the biomarker data ofeach segment with fingerprint data for said condition, and recordingdeviation measures between said the fingerprint data and the biomarkerdata.
 10. A neural response system as claimed in claim 9, whereinrecording the deviations includes summing the deviations, and thediagnostic tool compares sums with the fingerprint data for thebiomarkers.
 11. A neural response system as claimed in claim 1, whereinthe biomarkers represent a comparison between a background phase and anacceleration or deceleration phase of the response signals.
 12. A neuralresponse system as claimed in claim 1, including a tilt chair forsubjecting the person to a plurality of tilt sequences, and at least oneelectrode connected to at least one ear of the person and an amplifiercircuit to record the tilt response signals produced in response to eachneural sequence.
 13. A neural response system as claimed in claim 12,wherein the tilt sequences include at least one of up/down, front/back,ipsilateral, contralateral, and rotation.
 14. A neural response systemas claimed in claim 13, wherein the up/down and rotation sequencesincludes sequences with the patient upright and sequences with theperson prone.
 15. A neural response system as claimed in claim 14,wherein electrodes are connected to each ear of the person to record theneural response signals produced in response to each tilt sequence forthe left ear and the right ear.
 16. A neural response system as claimedin claim 1, wherein the biomarker data indicates whether the person hasat least one condition being a neurological disorder and/orneurodegenerative disease.
 17. A neural response system as claimed inclaim 16, wherein the condition includes one of benign positionalparoxysmal vertigo (BPPV), Meniere's disease, Parkinson's disease,Schizophrenia, depression, BiPolar Affective Disorder, Alzheimers,Dementia, Attention Deficit and Hyperactivity Disorder, MultipleSclerosis, Huntington's Chorea and Creutzfeldt Jakob disease.
 18. Aneural response system as claimed in claim 1, wherein the biomarker dataindicates an effect arising from administration of a pharmaceuticaland/or physical therapy.
 19. A neural response system as claimed inclaim 1, wherein the biomarker data is used to differentiate a diagnosisbetween conditions having similar symptoms.
 20. A neural response systemas claimed in claim 19, wherein the conditions are benign positionalparoxysmal vertigo (BPPV) and Meniere's disease.
 21. A neural responsesystem as claimed in claim 19, wherein the conditions are clinicaldepression and a depressive phase of a BiPolar Affective Disorder.
 22. Aneural response process, including: receiving and filtering, usingdifferent types of filters, a plurality of neural response signalsobtained from a person under different conditions and filtering theneural response signals with each of said filters; segmenting thefiltered response signals into time segments; and processing each of thetime segments to obtain and generate biomarker data representing aplurality of biomarkers for each segment, the biomarker for determiningwhether said person has a condition.
 23. A neural response process asclaimed in claim 22, wherein the neural response signals are obtainedfrom at least one electrode connected to at least one ear of the personsubjected to a plurality of tilt sequences in a tilt chair.
 24. A neuralresponse process as claimed in claim 22, wherein the filters include atleast one of a notch filter to substantially pass all frequencies, afirst high pass filter and a second high pass filter.
 25. A neuralresponse process as claimed in claim 24, wherein the cut-off frequencyfor the first filter is about 5 Hz and the cut-off frequency for thesecond filter is about 120 Hz.
 26. A neural response process as claimedin claim 22, wherein said processing generates curve data representing aSp/Ap field potential curve for each segment.
 27. A neural responseprocess as claimed in claim 26, wherein the biomarker data is determinedusing the curve data and the biomarkers represent relationships andconstants associated with the field potential curve.
 28. A neuralresponse process as claimed in claim 26, wherein the biomarker data isdetermined using the curve data and the biomarkers represent spikerates, and time and voltage measurements of the field potential curve.29. A neural response process as claimed in claim 26, wherein thebiomarker data is determined using the curve data and the biomarkersrepresent ratios, angles and areas associated with the field potentialcurve.
 30. A neural response process as claimed in claim 22, includingcomparing the biomarker data of each segment with fingerprint data forthe condition, and recording deviation measures between said thefingerprint data and the biomarker data.
 31. A neural response processas claimed in claim 30, wherein recording the deviations includessumming the deviations, and the sums are compared with the fingerprintdata for the biomarkers to determine whether said person has saidcondition.
 32. A neural response process as claimed in claim 22, whereinthe biomarkers represent a comparison between a background phase and anacceleration or deceleration phase of the response signals.
 33. A neuralresponse process as claimed in claim 22, wherein the tilt sequencesinclude at least one of up/down, front/back, ipsilateral, contralateral,and rotation.
 34. A neural response process as claimed in claim 33,wherein the up/down and rotation sequences includes sequences with theperson upright and sequences with the person prone.
 35. A neuralresponse process as claimed in claim 34, including connecting electrodesto each ear of the person to record the neural response signals producedin response to each tilt sequence for the left ear and the right ear.36. A neural response process as claimed in claim 22, wherein thebiomarker data indicates whether the person has at least one conditionbeing a neurological disorder and/or neurodegenerative disease.
 37. Aneural response process as claimed in claim 36, wherein the conditionincludes one of benign positional paroxysmal vertigo (BPPV), Meniere'sdisease, Parkinson's disease, Schizophrenia, depression, BiPolarAffective Disorder, Alzheimers, Dementia, Attention Deficit andHyperactivity Disorder, Multiple Sclerosis, Huntingdon's Chorea andCreutzfeldt Jakob disease.
 38. A neural response process as claimed inclaim 22, wherein the biomarker data indicates an effect arising fromadministration of a pharmaceutical and/or physical therapy.
 39. A neuralresponse process as claimed in claim 22, wherein the biomarker data isused to differentiate a diagnosis between conditions having similarsymptoms.
 40. A neural response process as claimed in claim 39, whereinthe conditions are benign positional paroxysmal vertigo (BPPV) andMeniere's disease.
 41. A neural response process as claimed in claim 39,wherein the conditions are clinical depression and a depressive phase ofa BiPolar Affective Disorder.
 42. (canceled)